Abstract

Evidence of outperformance garnered through factor investing is abundant through many sources. Typically, these accepted factors have been shown to add alpha to an index. Although market volume is a crucial piece of investment information, the majority of the public ignores volume as an investment factor. This paper introduces a new factor exhibiting alpha generation: the volume factor.

Introduction

Presently baby boomers are piling money into the stock markets preparing for their upcoming retirements. According to Forbes Financial Council, over the course of the next decade, ten thousand baby boomers will retire per day on average. Meanwhile the highest earnings demographic, the millennial population, notorious for doing things ten years late, is just beginning to gear up their investment saving plans. How are these new fund flows being allocated? According to CNBC, passive investing now accounts for 45% of all United States stock funds, up from 25% just a decade ago. Over the past few decades, capital weighted indexes have become America’s de facto investment option. It is not that passive investment strategies conducted primarily through capital weighting are a poor choice. To the contrary, capital weighting is a type of cross-sectional momentum investing that has shown excellent results. In a capital weighted index, as index members gain or lose relative momentum, they rise or fall in their weight rankings. With the vast allocation of these new net inflows being invested in this mindless strategy, holdings are becoming ever more concentrated. Currently (October 2021), the top five holdings of the S&P 500 (AAPL, MSFT, GOOGL/GOOG, AMZN, FB) account for over 22% of the index’s weightings.

Consequently, baby boomers, largely invested in the S&P 500, could be subjecting themselves to the risk associated with the sequences of returns or reverse dollar cost averaging when they begin selling their investment assets to supplement their lifestyle in retirement. According to Forbes, millennial investors despite being the youngest demographic, are actually the most risk averse group of all the generational demographics. Thus, they are likely to be fickle investors in a less favorable investment climate. Far and away, these two demographics represent the largest percentage of the American investment population. Combining these risks via the sequence of returns for baby boomers coupled with the risk aversion of millennials, multiplies the probability as well as the volatility associated with an S&P 500 unwinding event. Such an event would be especially devastating to those employing this passive index strategy and to those holding large concentrations of individual issues heavily weighted within the S&P 500.

As opposed to mindlessly following the movements of the herd, factor investing provides an alternative investment strategy to passive investing. Factor investing involves choosing or weighting investments based on their characteristics or attributes. Think about factor investing like screening a group of candidates. A hiring manager may desire candidates with certain levels of experience or education. Other options might be more subjective such as demonstrating leadership, being highly motivated and able to follow directions. Likewise, equities attributes might be fundamental (the underlying company) in nature such as earnings, profitability, cash-flow and revenues. While other attributes are more technical (shareholder behavior) such as price momentum and volatility. Still other attributes may not be as easily characterized as either singularly fundamental or technical such as dividend and size characteristics. According to Blackrock, presently, five broad factor categories exist: value, size, quality, momentum, and low volatility.

Evidence of outperformance garnered through factor investing is abundant through many sources. Typically, these accepted factors have been shown to add alpha to an index. Although these traditional factors may provide incremental improvement, this paper introduces a new factor exhibiting alpha generation. This paper is devoted to that factor - volume. When properly understood within the context of price trends, volume reveals the forces of supply and demand. When uncovered and applied correctly, this information could very well be the most prominent factor in price discovery to date.

In this paper, the reader is introduced to the Volume Price Confirmation Indicator (VPCI) and Capital Weighted Volume. The VPCI reveals the asymmetry between price trends and volume weighted price trends. The information derived from the VPCI indicator will empower us to rank securities according to their strength and persistence of volume confirmation. Capital Weighted Volume on the other hand reconciles price indexes with their corresponding volume flows. The accumulation of this flow data over time reveals the trends of capital in and out of their respective indexes. These capital flow trends may be useful in characterizing a given indexes investment forecast as being either favorable or unfavorable.

From the information presented from this paper, the reader will come to understand the power of volume as a truly unique investment factor. However, before we introduce the testing results, let us begin by reviewing the rationale of volume as an investment factor. We begin our study by introducing volume and how it relates to its sibling price within market trends.

Price and Volume

In the exchange markets, price results from an agreement between buyers and sellers, despite their different appraisals of the exchanged item’s value. One opinion may offer legitimate fundamental grounds for evaluation, while the other may be pure nonsense. To the market, however, both are equal. Price represents the convictions, emotions, and volition of investors. It is not a constant, but rather changes and is influenced over time by information, opinion, and emotion.

Market volume represents the number of shares traded over a given period. It is a measurement of participation, enthusiasm, and interest in a security. Think of volume as the force that drives the market. Volume substantiates, energizes, and empowers price. When volume increases, it confirms price direction; when volume decreases, it contradicts price direction.

In technical analysis theory, increases in volume generally precede significant price movements. An intrinsic relationship exists within these two independently derived variables, price and volume. When examined together, price and volume give indications of supply and demand that neither could provide independently. This relationship is what the volume factor is all about.

Volume is the Force

"A Jedi’s strength flows from the force.” -Yoda

Although market volume is a crucial piece of investment information, the majority of the public is ignorant of volume. Fundamental analysts often do not consider volume, while technical analysts underutilize it. Yet volume provides essential information in two critical ways: (1) by indicating a price change before it happens and (2) by helping the technician interpret the meaning of a price change as it happens.

Volume Leads Price

Although practitioners of technical analysis and academia have often been at odds, volume information is one area where they tend to largely agree. Volume can provide essential information by indicating a price change before it happens. The message is extremely telling, particularly when the volume reaches extreme levels. During such times, volume offers far superior information than price alone could ever provide. Gervails, Kaniel, and Minglegrin authors of “The High Volume Return Premium,” a white paper from the University of Pennsylvania’s Rodney L. White Center for Financial Research, state, “We find that individual stocks whose trading activity is unusually large (small) over periods of a day or week, as measured by trading volume during those periods, tend to experience large (small) subsequent returns.” These researchers further state, “A stock that experiences unusually large trading activity over a particular day or a week is expected to subsequently appreciate.”

Figure 1 The High-Volume Return Premium

Illustrated in Figure 1 are the testing results of Wharton’s 33-year study comparing stocks that experience relatively high-volume surges compared to normal and low-volume stocks. Similar conclusions were confirmed by Kaniel, Li, and Starks of the University of Texas. Their research paper, “The High Volume Return Premium and the Investor Recognition Hypothesis: International Evidence and Determinants,” concludes, “We study the existence and magnitude of the high-volume return premium across equity markets in 41 different countries and find that the premium is a strikingly pervasive global phenomenon. We find evidence that the premium is a significant presence in almost all developed markets and in a number of emerging markets as well.”

Volume Interprets Price

The second critical way in which volume provides information is by helping the technician interpret price. Volume enables the analyst to interpret the meaning of price through the lens of the corresponding volume. The authors Blume, Easley, and O’Hara (1994) reported in the Journal of Finance “Market Statistics and Technical Analysis: The Role of Volume”, “volume provides information on information quality that cannot be produced by the price static”. These researchers demonstrate how volume, information precision, and price movements relate, as well as how sequences of volume and prices can be informative. Moreover, they also show that traders who use information contained in market statistics do better than those trades who do not. Thus, technical analysis arises as a natural component of the agents learning process.

Nonetheless, price alone represents the vast majority of the work within technical analysis. Thus, this purpose of this paper is to grant the volume factor the significance volume is due as an essential element of investment analysis. However, doing so without also discussing price is also insufficient. Volume cannot be properly understood without price any more than price can be adequately assessed without volume. Independently, both price and volume convey vague market information. However, when examined together, they provide indications of supply and demand that neither could provide independently. Ying (1966), in his groundbreaking work on price-volume correlations, stated, “Price and volume of sales in the stock market are joint products of a single market mechanism; any model that attempts to isolate prices from volumes or vice versa will inevitably yield incomplete if not erroneous results.” Two similar and related volume category types are tick based and volume weighted indicators.

Tick Based Indicators

An exchange market works much like an auction, where price is formed by two counter parties, each with a different opinion about the security's future price direction, who agree to exchange a financial instrument. If the agreement occurs on an uptick, the buyer has applied more demand than the seller exerts to supply. Likewise, if the agreement occurs on a downtick, the seller's actions wields greater force than those of the buyer. Through tick volume, one can decisively quantify the relationship between price and volume.

Don Worden, president and founder of Worden Brothers, developed the concept of Money Flow in the late 1950s under the name "Tick Volume." Today, Money Flow is primarily popularized by Laszlo Birinyi. When investors use the term "tick," they are referring to an individual trade. An uptick, or +tick, is a trade that occurs at a price higher than the previous trade. A downtick, or -tick, is a trade that occurs at a lower price than the previous trade. Tick volume refers to the volume of shares traded per tick. Tick volume analysis evaluates the change in price and volume on a tick-by-tick basis. Uptick volume is the volume that occurs on upticks. Likewise, downtick volume is the volume occurring on downticks. Where it gets muddy is in the common instance of trades that occur at the previous price - an unchanged tick. In such a scenario, the commonly accepted view is to treat the unchanged tick volume as if it were a part of the previous tick. Thus, if the previous tick was up, the unchanged tick's volume would also be considered as uptick volume and vice versa.

Price-weighted tick volume uses tick data to weight each trade's volume by its corresponding price. The upticks are subtracted from the downticks and accumulated over time. In essence, Tick Volume/ Money Flow is volume weighted by the corresponding price accumulated on a tick-by-tick basis:

Tick Volume (aka Money Flow) = Cumulative Sum (Tick Price * Uptick's Volume) - Cumulative Sum (Tick Price * Downtick's Volume)

This calculation measures the supply relative to the demand on a per-trade basis and accumulates the difference over time. It reveals whether money is flowing into or out of the stock based on upticks being buys and downticks being sales. For example, we use two ticks to calculate Money Flow. The first tick goes through on an uptick of 100 shares at $100. Immediately, the next tick goes through on a downtick at $99.99 on 10,000 shares. The Money Flow is $10,000 (($100 *100 shares) - $999,900($99.99 * 10,000)), meaning that $989,900 (999,000 -10,000) more was sold than purchased in the stock. From this illustration, one can see how Money Flow wildly veers from the price direction by giving stronger weight to larger volume transactions. This information is used much in the same way as other volume indicators. When Tick Volume / Money Flow rises, it suggests demand is building, indicating the price might rise. When Tick Volume falls, it suggests that supply is building, an indication that the price might fall.

However, the increase in automation of the exchange markets combined with the decimalization of security prices has strongly reduced the reliability of this form of intraday analysis. Trades filled by scalpers and market makers are most often filled from existing inventories, making the concepts of accumulating up and downticks much more obscure. Additionally, institutions normally "work" their block trades throughout the course of the trading session making their activities less transparent to the public. Often this practice includes selling into upticks at the offer and buying into downticks at the bid further skewing the data.

The next development in tick based analysis was Volume-Weighted Average Price. The VWAP was first introduced to the trading community in the March 1988 Journal of Finance article, “The Total Cost of Transactions on the NYSE” by Stephen Berkowitz, Dennis Logue, and Eugene Noser. VWAP is the average price at which investors have participated over a given time period, which is typically one trading day. This is calculated by multiplying and dividing the total by the number of shares traded: placing each price tick by the corresponding volume, and then summing the results of all these trades

VWAP = Sum of Trade's Price * Trade's Volume / Sum of Trading Volume

The VWAP is used more as a statistic than an indicator. It is the industry standard to determine a security’s accumulation or distribution throughout the trading session. VWAP is the benchmark utilized to compare the average price actually paid to the average price all investors paid for the stock throughout the trading day. Following the VWAP assists institutions in reducing the impact of their large trading operations.

The next innovation in this category of volume analysis is Volume Weighted Moving Averages or VWMAs. Volume weighted moving averages advance the concepts of both VWAP (tick based “reflections of time”) and Tick Volume (tick based accumulations) applying a much more flexible approach. Like tick volume and VWAP, VWMAs calculates average fund flows into and out of securities. Also, unlike tick-volume VMWA’s are not accumulation indicators. And unlike VWAP, VWMA’s are not reset in the beginning of a new trading period. Moreover, VWMAs can be either tick based or time based in its calculation, but more commonly time.

This example is in days but VWMAs can be set to any time frame (minutes, weeks, months), ticks or trading block sizes. The VWMA is calculated by weighting each frame's (time, tick or block) closing price with the frame's (time, tick or block) volume compared to the total volume during the range:

Volume-Weighted Average = Sum {Closing Price (I) * [Volume (I) / (Total Range)]}, where I = given action.

Because volume leads price, it makes sense to introduce volume into momentum indicators to make them even faster. Because volume confirms price trends, volume weighting can enhance trend indicator’s reliability. Likewise, because volume leads price, one can combine momentum with volume information to create indicators that provide quicker and more reliable signals. This leads us to the next innovation in volume weighting analysis, the Volume Price Confirmation Indicator or VPCI.

Volume Price Confirmation Indicator

Now what if there were a way to look deep inside price and volume trends to find out whether or not current prices are supported by volume? This is the objective of the Volume Price Confirmation Indicator (VPCI), a methodology that measures the asymmetry between price and volume trends.

Many technical indicators have been developed to decode the price volume relationship. However, the key to grasping volume information is not the volume data alone or volume’s direct relationship with price movements. Rather, this interrelationship is best understood in the context of volume’s relationship within the price trend. The VPCI was uniquely developed to unveil critical information from this volume/price relationship within trends.

The VPCI exposes the relationship between the prevailing price trend and its corresponding volume, as either confirming or contradicting the price trend. This information gives possible indications of impending price change.

The VPCI determines the asymmetry between price trends and volume weighted price trends. This is primarily derived by examining the difference between a volume-weighted moving average (VWMAs) and the corresponding simple moving average (SMA). These differences expose information about the inherent relationship between price trends and volume flow trends. Although moving averages demonstrate a stock’s changing price levels, they do not reflect the amount of investor participation. With VWMAs, however, price emphasis is adjusted proportionally to each day’s volume and then compared to the average volume over the range of study.

Confirming Signals

Fundamentally, the VPCI reveals the proportional imbalances between price trends and volume-adjusted price trends. Several VPCI signals may be employed in conjunction with price trends and price indicators. These include a VPCI greater than zero, which shows the relationship between price trends and volume as either confirming (when above zero) or contradicting (when below zero) the price trend.

A rising or falling VPCI provides trend direction, revealing the trend of volume confirmation or contradiction. A smoothed volume-weighted average of VPCI, called “VPCI smoothed,” demonstrates how much the VPCI has changed from previous VPCI levels and is used to indicate momentum. Bollinger Bands may also be applied to the VPCI, exposing VPCI extremes. We will expand on this tactic later.

VPCI Most Bullish Volume Index

Volume is most useful during extremes. The VPCI Most Bullish Volume Index follows the stocks in the index with the strongest bullish confirmation. This Index is calculated by selecting only the top decile VPCI stocks within the S&P500 index. Stated another way, the Most Bullish Volume Index comprises the stocks containing the top 10% highest weekly VPCI readings within the S&P500. At the beginning of each quarter, new stocks are purchased upon breaking into the top 10 percent list. Likewise, holdings falling out of the top 50% of VPCI scores are sold at the beginning of the quarter. The sold issues are then replaced with the securities with the highest VPCI scores in the top 10% of the S&P 500 index that are not already included in the holdings.

A test was performed on the individual members of the S&P 500 Index from January 1, 2000, through December 31st, 2019. The testing results were verified by third-party verification service Ned Davis Research and not optimized in any way. Excluding dividends, the S&P 500 benchmark annualized returned was 6%. In contrast, the annualized return of the most bullish volume index was 8.8% for the period (see Figure 3). This volume factor, VPCI’s Most Bullish Index, represents an annualized outperformance of 2.8% over the S&P 500 index over the last two decades.

Figure 2 VPCI Most Bullish Volume Index

Applying Volume Analysis to Indexes

So far, we have covered the evolution of tick volume to VWMAs and then moved to volume spread trend analysis with the VPCI. These are useful tools in security analysis of individual securities but what about indexes? Indexes are not bought and sold like securities but rather are comprised by the movements of their individual components. Thus, measuring supply and demand via volume analysis must be reevaluated to account for the unique structure of price indexes which are truly a “sum of the parts” as opposed to a freestanding trading vehicle.

Herein lies the main issue of applying volume analysis to indexes. The data between index volume totals and price indexes are not homogeneous because price indexes are weighted, and volume totals are tallies. Take, for example, a stock in an equal-weighted index that has a 2 percent price increase. This 2% change in the equal-weight S&P 500 Index accounts for a 0.00004 (.02 * 1/500) change in the price index. However, a similar change in volume rarely has the same effect. Continuing with the prior example, let's say the volume of the stock increases by 2%. Thus, the stock price and volume have both increased by 2%. However, it is highly unlikely that the 2 percent proportional increase in stock volume is equally proportional in the S&P 500 Index's total volume computations. This occurs because price indexes are weighted while volume totals are tallied.

As a further example, a stock in the price index undergoes a three for one reverse split. The split has no impact the components weighting in the price index yet its volume will most likely triple all things being equal. In this way, low priced issues generally dictate index volume tallies. However, the opposite is generally true in price indexes as the largest capitalized components gather the highest weightings.

At best, volume totals are a simple tally of all 500 individual components' volume added together. More likely though, the displayed S&P 500 volume on one’s chart monitor is not even the S&P 500 volume at all but typically the volume of all the New York Securities Exchange listed issues! Most investors do not realize when they look at a S&P 500 Index volume chart, the top weighted components like Apple, Microsoft, Facebook, Amazon, and Google(s) are likely not included in the volume tallies displayed on the bottom of the chart because these issues all trade on the Nasdaq.

A tool partially assisting in overcoming some of these faults is Dollar Volume. Dollar Volume is a tally of each index members share price multiplied by the volume. Dollar volume assists in the discrepancies between low-priced stock issues generally having lower price weightings but higher volume tallies. Still Dollar Volume does not address the weighting discrepancies with the corresponding indices. Yet, a central theme conveyed throughout this paper is that volume is best understood in relationship to price.

With this price -volume relationship in mind, it is important to understand the differences between how price indexes and volume totals are compiled. Prices indexes are calculated through summing the individual performance of each component member in accordance with its weighting within the index. Many methods exist to determine this weighting, including capitalization, equal weighting, revenue, dividend weighting, and an endless array of other possibilities. Typically, though, weighting is done by market capitalization i.e. how much each company is proportionally worth to the collective whole. A company's capitalization is calculated by multiplying the number of shares available for sale (shares outstanding) times the stock's price. As a result, in a capital weighted index, the companies that are worth more have a larger pro rata influence on the index. Likewise, the companies with lower values have a smaller pro rata influence on the index.

The solution devised to restore the relationship between price and volume in indexing is capital-weighted volume. Capital weighted volume weights each individual issue's volume according to the issue's price-capital weighting in the underlying index or exchange. Thus, if a company is a larger, more influential component of the index, then its corresponding volume is reflected pro rata in accordance with the component member's larger size. Likewise, a smaller less significant company's volume is also reflected pro rata in accordance with its smaller capitalization. In this way, a component's volume is equally represented with respect to its capital weighted price influence on the index or exchange.

Calculating Capital Weighted Volume:

Step 1: Calculate each components Capital Weighting
Price * Shares Outstanding

Step 2: Determine each components Index Weighting
Capital Weighting / Indexes Capital Weighting

Step 3: Calculate each components Capital Weighted Volume
Volume * Capital Weighting

Step 4: Sum & Parse Upside VS Downside Volume Tallies by Component

Step 5: Add Upside + Downside CW Volume = Total Capital Weighted Volume

Step 6: Subtract Upside – Downside CW Volume & accumulate difference overtime = CW Volume Accumulation

Figure 3

Using weekly data, the capital weighted volume strategy takes a long position when accumulated capital weighted volume is above its 50-week exponential moving average. Upon a cross-under of accumulative capital weighted volume beneath its 50-week exponential moving average, the strategy moves from the investor from S&P 500 and into Treasury bills. Once capital weighted volume rises above its 50-week exponential moving average, the strategy returns the investor long the S&P 500 again.

Figure 4 Performance of Cap- Weighted Volume January 1st, 2000 – December 31st, 2019

The following study covers the past two decades (January 1st 2000 -December 31st 2019) and has been verified by third party Ned Davis Research. One can see that this system returned roughly the same return as being long only the S&P 500 x, 6.5% -vs- 6% in favor of the capital weighted volume trend. However, due to the volume factor, the risk assumed to achieve the return is significantly less following the trends of capital-weighted money flow. The volatility (standard deviation) of the long only strategy is 11% compared to 17.2% with buy and hold. Moreover, in isolating downside deviation, the capital weighted volume trend strategy is 7.9% versus the S&P500’s 12.3%.

These statistics reflect the strategy’s ability to retain capital and reduce risk. Further evidence is provided by drawdown. The capital weighted volume strategy’s largest drawdown is roughly half of buy and hold. Capital weighted volume only lost a maximum of 28.4% compared to a maximum drawdown of -54.7% with the S&P500. With respect to risk adjusted rates of return, the capital weighted volume strategy far exceeded buy and hold as illustrated by its Sharpe Ratio of 0.44 contrasted to 0.25 for the S&P500. Due to the lower risk of the strategy, an investor would experience a much smoother ride and thus be more likely to stay the course through multiple market cycles. Perhaps even more important, an investor requiring income via principal withdrawals (a retiree for example) would not be exposed to near the drawdown allowing the portfolio to withstand a higher and more sustainable withdraw rate. We will come back to this final point later.

The VPCI V Bottom

This evidence suggests that the capital weighted volume system is excellent at trend following. That stated, bear markets tend to over-correct and then bounce back sharply. Consequently, identifying the next bull market entry point through trend analysis may cause investors to leave too much profits on the proverbial table. This is where volume analysis shines with its ability to identify when capitulation points come into play. To identify capitulation entry points we will once again return to the VPCI.

A bear market is driven by fear and portrayed by a falling price trend. A falling price trend without volume is apathy, fear without increasing energy. Unlike greed, fear is self- sustaining and can endure for long periods often without increasing fuel or energy. Adding energy to fear is likened to adding fuel to a raging fire. In such cases, weak-minded investors are overcome by fear becoming irrational until the selling climax reaches a state of maximum homogeneity. At this point, the ownership held by the weak investors is being purged, producing a type of heat death. These occurrences are visualized by:

• Price index falling 10% or more from its 26 week peak
• Capital Weighted Volume falling beneath trend
• The VPCI readings dropping below .4
• The VPCI falling below its lower standard deviation band (Bollinger Band)

Together these conditions often indicate that the market is poised for capitulation. By price falling 10% or more tells us the market is in a correction phase. When capital weighted volume is below trend, capital flows are trending out of the market. A VPCI reading of negative 4 or less, suggests the market is in a severe fire, sale high-volume decline as the volume price relationship is severally stressed. Over the past two decades, an ultralow VPCI reading of -.4 or less occurs less than 1% of the time. Similarly, the VPCI being below its two standard deviation band indicates the indicator is at a short-term extreme (occurrence approximately 5% of the time).

Sirius is called the morning star because it appears at the darkest time right before the light of dawn, during the “dog days” of summer. After the above “dog days” oversold conditions are met, our morning star reentry trigger occurs when the VPCI reverses direction rising upwards back above (crossing over) its lower Bollinger Band forming a “V” bottom.

An item of note, because index volume is a faulted gauge for reasons covered in the prior section, index volume is not used to produce a VPCI V bottom signal. Alternatively, exchange traded funds (ETF) data is used in lieu of index data. I have found ETF volume data to be a superior data set in market extremes, especially declines. Because ETFs are commonly used by individual investors, they are highly subject to the emotional swings amplifying the signals. In large declines, investors often turn to broad market index products for quick and liquid execution of long entries as well as for hedging. V bottoms are rare events in the broad markets. Since the development of the VPCI in 2002, a VPCI V bottom has marked most every major intermediate term broad market bottom in the S&P 500 SPY ETF since its discovery in 2003 (see addendums 1-12).

Figure 5 February 3rd, 2003 VPCI V Bottom

Figure 6 March 9th, 2009 VPCI V Bottom

The problem with traditional trend following systems is not that they often fail to avoid bear market down turns. Applied in isolation, trend following almost always misses the new bull market’s birth, which is often the strongest, most power point of the advance. In theory, infusing VPCI V bottoms into our capital weighted volume trend strategy creates a system where not only can investors enjoy the steadier ride of upward trend following while side stepping much of the declines, but additionally reenter the bull birth while prices are still relatively low. (See Figures 5 & 6 above)

The following strategy Bull Run Bear Hide, combines following capital weighted volume trends with the VPCI V bottoming tool. The testing period was the prior two decades, January 1st, 2000 to Dec 31st, 2019. Long and reentry conditions included 1) capital weighted volume is above its 50-week exponential moving average (EMA) or 2) a VPCI V Bottom on the SPY ETF. To review, a VPCI V bottom occurs when the VPCI crosses back above its lower Bollinger Band after falling below -.4. When either of these conditions are true (Bull Run), our strategy is 100% invested in the S&P500 Index. If neither of these conditions are true, then the strategy is 100% in T-bills (Bear Hide).

The results are shown in Figure 9 below. Up arrows signal an upward crossover of Capital Weighted Volume above its 50-week EMA. Down arrows signal a downward cross-under of Capital Weighted Volume below its 50-week EMA. VPCI V Bottoms are signified by the letter “V”. The S&P 500 is colored green when long and red when in T-Bills.

Figure 7 Bull Run Hide Strategy 2000 -2020

The following test results are verified by third party Ned Davis Research. The trend following plus the bottom-seeking system has produced a return of 9.5% over the past two decades compared to the buy and hold strategy’s return of 6.0%, an annualized improvement of 3.5%. Although these returns are impressive in their own right, the practicality of an investor tolerating the emotional swings of an investment strategy is an even more relevant factor in determining financial outcomes. Financial outcomes should be the ultimate goal in portfolio management as well as financial planning. The Bull Run Bear strategy significantly improves the passive indexing approach as indicated in the risk statistics. The standard deviation drops from 18.9% passive to 15.6% active. Parsing out upside volatility, downside deviation improves from 13.4% to 10.9% with our Bull Run Bear Hide Strategy. The Sharpe Ratio more than doubles buy and hold, from 0.23 to 0.50 indicating a significantly improved risk adjusted rate of return.

Surveys show millennial investors spooked by the events of 2008 and 2009, and the lost decade of 2000 to 2009, are more risk averse than previous generations. By eliminating some of the volatility risk and providing downside protection, this Bull Run Bear Hide strategy delivers a softer less volatile experience for the risk adverse investor. Perhaps even more importantly to the baby-boomers who are entering into their retirement phase at a record 10,000 per day clip. A high percentage of these baby-boomer investors will draw from their capital investments to supplement their retirement income. It is often in these withdrawal situations that too much of the emphasis is on portfolio returns when the goal should be positive financial outcomes and tolerable experiences.

Investment strategies with large drawdowns are entirely unsuitable for investors needing cashflow. Table 1 on the next two pages examines an investor desiring a 1% quarterly distribution, to supplement their retirement income needs.

Table 1 1% Quarterly Distributions Passive -vs- Bull Run Bear Hide Strategy

Table 1 illustrates an investor retiring with $1 million invested in the S&P 500 starting in January 2000. The investor will withdraw a quarterly 1% distribution to supplement his or her retirement income through either a passive investment or by following capital weighted volume trends combined with the VPCI V bottoms strategy (Bull Run Bear Hide).

Both the passive and active strategies started with an income of $10,229.68 in the first quarter of 2000. The passive approaches quarterly income was cut nearly in half by the end of the third quarter of 2002, to only $5,205.77. Later in the first quarter of 2009, the passive investors income hit a distribution low of $4,434.28. Although the passive investor finishes the fourth quarter of 2019 at an all-time distribution high of $14,454.98, many life experiences would have been sacrificed at the altar of volatility not to mention the emotional stress endured, especially through the lost decade of 2000 to 2009.

We now return to our prior 1% quarterly distribution example, but this time employing the Bull Ride Bear Hide strategy employing Capital Weighted Volume with VPCI V bottoms as opposed to the passive approach. When the passive S&P500 investor hits it’s 2002 third quarter low of $5,502.77, our capital flows strategy returns the investor nearly all their beginning distribution, $9,839.01. When the S&P 500 investor hit their all-time low of $4,434.28 in March 30th, 2009, again the capital flow strategy returned $9,969.73, more than doubling the passive index investors distribution on the same date.

The lowest distribution created by following the Bull Ride Bear Hide capital fund flows strategy was suffered 2nd quarter of 2000 @ $9,200.86 again more than double the index strategy low watermark distribution ($4,434.28). Like the passive index strategy, the capital flows strategy all-time high occurred December 31st, 2019 @ $27,718.31 almost doubling (>90%) the quarterly income distribution of the passive index strategy high watermark ($14,454.98).

Over the course of the first 20 years of retirement, the passive index investor collects $673,300 for his or her spending needs. In contrast, the tactical investor following the trends of capital flows withdrawals tallies a total disbursement of $1,156,817 thus creating significantly better cashflow to enjoy over the course of their retirement. Moreover, if the retiree were to pass away at the end of the study, the active approach would provide a legacy of $2,744,113 nearly tripling the investors million-dollar starting point. This compares to the passive index investor ending with an estate of only $1,431,043.

Combining distributions with ending values, the investor employing the passive index without the tactical overlay gains $2,197,695 over the starting point. However, the investor employing volume factors through capital flows / VPCI V bottoms strategy more than doubles the total returns of the passive strategy adding to the original principal $5,131,778 over the last two decades. Thus, our active volume based approach provides far superior income, wealth, and peace of mind undoubtedly leading to better financial planning outcomes.

Conclusion

Factors are known drivers of portfolio risks and returns. Factors may be an intelligent alternative to the increasingly popular and saturated passive approach. In this paper, we proposed that volume also be included as an investment factor. This paper introduced two differentiated volume factor strategies each employing unique and differentiated volume indicators. The first strategy invests in factor selected individual components of the S&P 500 Index. The second strategy tactically gauges and trades the S&P 500 Index based on capital volume flows and volume capitulation points.

In the first volume factor studied the VPCI Most Bullish Volume Index, we purchased only individual stocks with the most bullish volume confirmation (top 10%) and held them until the volume indicator moved to price contraction (below 50%). We showed how this volume confirmation strategy produced highly profitable returns over the capital weighted S&P 500 index by nearly 3% per year over the course of the last two decades. Based on these test results, one can infer those stocks exhibiting the factor of extremely bullish volume confirmation as measured by the VPCI index significantly outperform the capital weighted index over a long cycle.

The next volume factor strategy Bull Run Bear Hide, followed the trends of volume flows moving in and out of the S&P 500 as measured through capital weighted volume. When capital weighted volume was above trend (Bull Run), the strategy invested in the S&P 500 index. When it fell below trend (Bear Hide), the strategy invested in T-bills until capital flows moved back above trend or a VPCI V bottom was triggered. Again, this volume derived strategy beat the passive buy and hold S&P 500 this time by more than 3% per year over two decades.

Not only did the tactical capital money-flows strategy provides essentially what most investors want, to participate in the market when it is rising and to avoid the market when it is falling. But more importantly, what most retirees need, steady and stable distributions protected from the ill effects of large drawdowns within the sequence of returns.

The alpha generated by properly assessing supply and demand through the volume tools introduced in this paper significantly increased returns far and above what is seen in passive investment and many of the best traditional market factors currently employed.

Moreover, the practical outcomes of employing the volume factor led to better outcomes for not only growth investors but for conservative and income investors as well.

Addendum 1 VPCI V Bottoms 2000 -2020

Addendum 2 May 2006 VPCI V Bottom

Addendum 3 March 2009 VPCI V Bottom

Addendum 4 August 2011 VPCI V Bottom

Addendum 5 August 2011 Weekly VPCI V Bottom

Addendum 6 Oct 16th, 2014 SPY, SPDRS S&P 500 Trust Series ETF

Addendum 7 August 27th, 2015 SPY, SPDRs S&P 500 Trust Series ETF

Addendum 8 September 2016 SPY, SPDRs S&P 500 Trust Series ETF

Addendum 9 February 2018 SPY, SPDRs S&P 500 Trust Series ETF

Addendum 10 October 2018 SPY, SPDRs S&P 500 Trust Series ETF

Addendum 11 January 2019 Weekly VPCI V Bottom, SPY SPDRs S&P 500 Trust Series ETF

Addendum 12 March 19h, 2020 SPY SPDRs S&P 500 Trust Series ETF

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